"author:Greeshma-19" matching MCP servers:

Enables users to train and compare Logistic Regression and KNN models on the Wisconsin breast cancer dataset, run predictions on patient feature inputs, compute confusion-matrix metrics and select the best model by malignant recall, generate global and local SHAP explanations, and export Parquet audit logs of every tool call. Also provides sample test-set inputs so agents can invoke prediction tools with valid 30-feature payloads.